Cited by 157Technology Adoption and User BehaviourInnovative Human-Technology InteractionGender and Technology in Education

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Predicting the use of online information services based on a modified UTAUT model

Oh, Jong-Chul, Yoon, Sung-Joon·2014·Behaviour & Information Technology

DOI 10.1080/0144929x.2013.872187

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Abstract

There is a growing consensus that the conventional technology acceptance model should be modified and expanded to provide a better understanding of the behaviour related to Internet services. Recognising this need, this study re-evaluates the utility of Venkatesh et al.’s [2003. User acceptance of information technology: toward a unified view. MIS Quarterly, 27 (3), 425–478] Unified Theory of Acceptance and Use of Technology (UTAUT) model. First, this study proposes a new modified model of technology acceptance by adding the concepts of trust and flow experience to the original UTAUT model. Second, the study investigates how the model's explanatory power changes for different types of Internet services. For this, this study considers two services – ‘e-learning’ and ‘online gaming’ – for their utilitarian and hedonic characteristics, respectively. The results of this study suggest that the proposed model can better explain behavioural intentions towards Internet services than the original model. The two variables – flow experience and trust – contributed to the overall significance of the model. Furthermore, the type of Internet service moderated the effects of the independent variables on behavioural intentions and use behaviour.

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Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Diffusion of Innovations 1
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · Routledge eBooks · doi:10.4324/9780203710753-35 · Cited by 37,670
Untitled work
(1975) · PhilPapers (PhilPapers Foundation) · Cited by 36,737
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
Diffusion of innovations
Valente, T. W. (2003) · Genetics in Medicine · doi:10.1097/01.gim.0000061743.67794.c4 · Cited by 20,559
Not So Different After All: A Cross-Discipline View Of Trust
Rousseau, D. M., Sitkin, S. B., Burt, R. S., & Camerer, C. (1998) · Academy of Management Review · doi:10.5465/amr.1998.926617 · Cited by 10,274

Show all 51 references

Research works printed but not linked: 4

Chang J., 2004, Korean Journal of MIS, 14, 94
Park S., 2005, Korean Journal of Marketing, 20, 21
Pavlou P.A., 2003, International Journal of Electronic Commerce, 7, 69
Zhou T., 2011, Behavior & Information Technology, 32, 163

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Authors: Oh, J.-C., & Yoon, S.-J.
Affiliations: Shin Ansan University (KR)
Kyonggi University (KR)
Corresponding author: Yoon, Sung-Joon
ORCID: Yoon, Sung-Joon
Venue: Behaviour & Information Technology
Publisher: Informa UK Limited
Published: 2014-04-07
Volume: 33
Issue: 7
Pages: 716-729
ISSN: 0144-929X (ISSN-L)
1362-3001
DOI: 10.1080/0144929x.2013.872187
OpenAlex: W1990390924
Cited by: 157
References: 51
Citations by year: 2026: 7 · 2025: 11 · 2024: 15 · 2023: 16 · 2022: 22 · 2021: 21 · 2020: 15 · 2019: 14 · 2018: 15 · 2017: 7 · 2016: 8 · 2015: 5 · 2014: 1
FWCI: 10.22
Type: journal article
Language: en
Open access: closed
Locations: Behaviour and Information Technology (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Social Sciences › Gender Studies › Gender and Technology in Education
Keywords: UTAUT, technology acceptance, online information services, trust, flow experience, online learning, online games, behavioral intention

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Predicting the use of online information services based on a modified UTAUT model

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